Hepatitis

Defining weight trajectory after liver transplantation using generative artificial intelligence.

A better understanding of weight trajectories in liver transplant (LT) recipients is essential to improving clinical outcomes. We utilized Generative Artificial Intelligence (GenAI) to identify and visualize factors that exist but are not observable (latent factors or LF) that result from limitations in current knowledge or statistical approaches to model weight in LT recipients. Using GenAI, weig...

Predictive modeling and fragment-based design of triterpenoid-nucleoside conjugates targeting coronavirus membrane fusion.

Triterpenoids are known for their broad biological activities, yet their potential against SARS-CoV-2 has not been fully elucidated. In this study, using an antiviral dataset generated from our experimental evaluation of triterpenoid-nucleoside derivatives that disrupt SARS-CoV-2 pseudovirus entry by targeting the fusion peptide-heptad repeat 1 (FP-HR1) interface of Spike, we developed a stacking ...

HeptaTB Dx: a diagnostic model leveraging cuproptosis-ferroptosis crosstalk for distinguishing latent from active tuberculosis.

UNLABELLED: Distinguishing latent tuberculosis infection (LTBI) from active tuberculosis (ATB) remains challenging. The roles of cuproptosis-ferroptos...

CoREST complex inhibition alters RNA splicing to promote neoantigen expression and enhance tumor immunity.

Epigenetic macromolecular enzyme complexes tightly regulate gene expression at the chromatin level and have recently been found to colocalize with RNA...

Machine Learning-Augmented Graphene Transistor Biosensing: Quantitative Platform Validation and Immunotesting of Hepatitis E.

Graphene-based chips face persistent sensor-to-sensor variability due to manufacturing defects and polymer contamination, limiting their analytical re...

Viral traits from deep mutational scanning and socio-demographic context predict SARS-CoV-2 lineage fitness across diverse countries.

OBJECTIVES: To assess the joint effects of SARS-CoV-2 viral traits (ACE2 binding, immune escape, and cell entry) and socio-demographic context on vira...

Morphological characterization and machine learning-based hyperspectral identification of naturally pigmented traditional Chinese starches.

As an intangible cultural heritage, food products derived from naturally pigmented traditional starches are facing a market trust crisis due to the ad...

The "A-B-C" Classification Reveals Outcome Trajectories in Patients With Hepatocellular Carcinoma Under Atezolizumab/Bevacizumab.

BACKGROUND & AIMS: We aimed to identify subgroups of patients with unresectable hepatocellular carcinoma (HCC) using a non a priori, data-driven machi...

Cinnamic acid derivatives in agrochemicals: current use and future perspective.

BACKGROUND: Cinnamic acid (CA) and its derivatives are widely used in various fields because of their robust, broad-spectrum biological activities and...

Integrating multiphase MRI surrogates to improve microvascular invasion detection and recurrence risk stratification in HCC.

BACKGROUND & AIMS: Microvascular invasion (MVI) is a key determinant of recurrence and poor outcomes in hepatocellular carcinoma (HCC), yet accurate p...

AI-designed PNA-peptide chimera overcomes suboptimal binding for dual inhibition of viral RdRp.

The chimera combining the peptide nucleic acids (PNAs) and peptides represent a promising bifunctional strategy by concurrently binding with protein c...

Revealing information from weak signals in electron energy-loss spectroscopy with a a deep denoiser.

Electron energy-loss spectroscopy (EELS) coupled with scanning transmission electron microscopy (STEM) is a powerful technique to determine materials ...

Structure-Based Classification of CRISPR/Cas9 Proteins: A Machine Learning Approach to Elucidating Cas9 Allostery.

The CRISPR/Cas9 system is a powerful gene-editing tool. Its specificity and stability rely on complex allosteric regulation. Understanding these allos...

Simulation-guided optimization of one-step gold nanoparticle amplification for paper-based detection of anti-IFN-γ autoantibodies.

Adult-onset immunodeficiency (AOID) caused by anti-interferon-γ autoantibodies (anti-IFN-γ Abs) lacks rapid, sensitive diagnostic tools suitable for f...

Novel Machine-Learning Models Outperform Noninvasive Tests in Metabolic Dysfunction-Associated Steatohepatitis With Fibrosis.

BACKGROUND & AIMS: Noninvasive tests (NITs) have not yet been systematically evaluated or optimized to detect metabolic dysfunction-associated steatoh...

Construction and validation of a hypertensive nephropathy diagnostic model based on mitochondrial-related genes using machine learning combined with WGCNA.

BACKGROUND: Hypertensive nephropathy (HTN) arises from chronic hypertension and may potentially result in severe renal failure. Due to the absence of ...

SE-PDS enhanced NIR spectral transfer learning: A machine learning approach for cross-instrument jet fuel property quantification.

This study proposes an improved Shared-Embedding-Enhanced Piecewise Direct Standardization (SE-PDS) algorithm to achieve near-infrared (NIR) spectral ...

Blood-based Vienna 3P/5P risk models accurately predict first hepatic decompensation in compensated advanced chronic liver disease.

BACKGROUND & AIMS: Invasive measurement of hepatic venous pressure gradient (HVPG) is the gold standard for diagnosing clinically significant portal h...

Amplification-free detection of mycoplasma pneumoniae via CRISPR-Cas12a and deep learning-optimized crRNAs on a lateral flow platform.

Accurate and rapid diagnosis of Mycoplasma pneumoniae infection is essential for reducing its significant health burden. An amplification-free CRISPR-...

Development and validation of an age prediction model using mRNA markers.

As a downstream product of transcriptional regulation, mRNA offers valuable insights into age-associated molecular changes and shows considerable pote...